Bankruptcy Prediction Based on Financial Data using PCA

Abstract

The survival of a company is a problem faced by every company operator and investor. It is very important to effectively predict the bankruptcy of a company. There are two problems in predicting company bankruptcy, one is the selection of eigenvectors, the other is the selection of prediction models. In this paper, based on the financial data of listed companies, the principal component analysis method is used to reduce dimensions and build a classification model to predict the bankruptcy of companies. It is found that the profitability, debt and liquidity of the company are significantly related to the bankruptcy of the company. In addition, it is found that the decision tree model has excellent prediction ability.